System, method and computer program product for packing

ABSTRACT

A computer-implemented wardrobe packing method, system, and a computer program product, include selecting a plurality of items stored in a memory to pack into a container, generating a packing order of the plurality of items based on packing preference data and item data stored in the memory, creating and displaying a video of step-by-step packing instructions for the plurality of items in the packing order, monitoring and comparing an actual packing process to a generated packing order, and controlling said displaying of step of the step-by-step packing instructions, in response to said monitoring and comparing.

BACKGROUND

The present invention relates generally to packing of items, and moreparticularly, but not by way of limitation, to a system, method, andcomputer program product for creating an interactive, augmented videodepicting an optimized packing order of wardrobe items.

Often, people conduct packing at the last minute, which leads to stress.In the last minutes of packing before a trip, people rush aroundgrabbing clothes even if they are not coordinated, or even forgetsomething important to pack.

Conventional packing strategies follow a set of rules based on the typeof item independently from all of the other items being packed. Forexample, packing to the minimum dimension of each item is not always thebest way of packing because each content has some preferences to pack.For example, blazers, coats, or shirts should be crease or wrinkle free.Therefore, folding blazers or coats are not the best way to pack becausepacking to the minimum dimensions leads to creases on the clothes.

Thus, the needs in the art include a wardrobe packing technique thatconsiders a packing preferences for each item individually to optimizethe packing space factoring in the packing preferences.

SUMMARY

In an exemplary embodiment, the present invention can provide acomputer-implemented packing method, the method including selecting aplurality of items stored in a memory to pack into a container,generating a packing order of the plurality of items based on packingpreference data and item data stored in the memory, creating anddisplaying a video of step-by-step packing instructions for theplurality of items in the packing order, monitoring and comparing anactual packing process to a generated packing order, and controllingsaid displaying of step of the step-by-step packing instructions, inresponse to said monitoring and comparing.

One or more other exemplary embodiments include a computer programproduct and a system.

Other details and embodiments of the invention will be described below,so that the present contribution to the art can be better appreciated.Nonetheless, the invention is not limited in its application to suchdetails, phraseology, terminology, illustrations and/or arrangements setforth in the description or shown in the drawings. Rather, the inventionis capable of embodiments in addition to those described and of beingpracticed and carried out in various ways and should not be regarded aslimiting.

As such, those skilled in the art will appreciate that the conceptionupon which this disclosure is based may readily be utilized as a basisfor the designing of other structures, methods and systems for carryingout the several purposes of the present invention. It is important,therefore, that the claims be regarded as including such equivalentconstructions insofar as they do not depart from the spirit and scope ofthe present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

Aspects of the invention will be better understood from the followingdetailed description of the exemplary embodiments of the invention withreference to the drawings, in which:

FIG. 1 depicts a high-level flow chart for a wardrobe packing methodaccording to an embodiment of the present invention.

FIG. 2 depicts a second high-level flow chart for the wardrobe packingmethod according to an embodiment of the present invention.

FIG. 3 depicts an exemplary implantation of the wardrobe packing methodaccording to an embodiment of the present invention.

FIG. 4 depicts a cloud computing node according to an embodiment of thepresent invention.

FIG. 5 depicts a cloud computing environment according to an embodimentof the present invention.

FIG. 6 depicts abstraction model layers according to an embodiment ofthe present invention.

DETAILED DESCRIPTION

The invention will now be described with reference to FIG. 1-6, in whichlike reference numerals refer to like parts throughout. It is emphasizedthat, according to common practice, the various features of the drawingare not necessarily to scale. On the contrary, the dimensions of thevarious features can be arbitrarily expanded or reduced for clarity.

With reference now to the example depicted in FIG. 1, a wardrobe packingmethod 100 according to an embodiment of the present invention includesvarious steps to optimize a packing order of items in order to create aninteractive augmented video while monitoring the users' packing processto display steps of the optimized packing order. As shown in at leastFIG. 4, one or more computers of a computer system 12 according to anembodiment of the present invention can include a memory 28 havinginstructions stored in a storage system to perform one or moreembodiments of the present invention.

Wardrobe packing in accordance with some embodiments of the presentinvention may give the impression of cognitive mental abilities andprocesses related to knowledge, attention, memory, judgment andevaluation, reasoning, and advanced computation. A system can be said tobe “cognitive” if it possesses macro-scale properties—perception,goal-oriented behavior, learning/memory and action—that characterizesystems (i.e., humans) generally recognized as cognitive.

Although one or more embodiments (see e.g., FIGS. 4-6) may beimplemented in a cloud environment 50 (see e.g., FIG. 5), it isnonetheless understood that the present invention can be implementedoutside of the cloud environment.

Referring again to the example depicted in FIG. 1, in step 101, aplurality of items from a wardrobe database to pack are selected.

The wardrobe database comprises a list of all of the items of the userthat the user may wish to pack. The wardrobe database can be manuallyupdated by scanning a Radio-Frequency Identification (RFID) of the itemwhen the user wants to enter an item into the wardrobe database.Preferably, the digital wardrobe can be linked to, for example, ashopping application such as an online website shopping cart, e-mail,etc. or a payment method. In this manner, the item is added to thedigital wardrobe when the item is purchased or payment is made.

Further, the digital wardrobe can be embodied as an application that theuser can view each item, edit user preferences for each item, and markeach item with characteristics. Preferably, the wardrobe database isembodied as an online view of everything that a user owns. In thewardrobe database, each item is associated with its dimensions, a typeof the item, a weight of the item, etc. (e.g., item data) and packingpreferences for the item (e.g., packing preference data).

For example, the item data comprises dimensions which includes a length,a breadth, and a height of the content, a type of the item whichincludes a category of the content such as whether it is a top, shirt,bottom, purse, shoes, etc., whether it is some fragile content likeglass bottles, laptops, etc., whether the item is a luggage bag (e.g., acontainer) that the items will be packed in.

Packing preferences include, for example, preferences with which someonewants to consider while packing such as an item to be crease or wrinklefree, an item to be packed at the top or bottom of the luggage bag, etc.

It is noted that each item includes a default preference until the userupdates the preference for the item. The default preferences can bedetermined based on, for example, crowd sourcing for preferences for theitem.

In the wardrobe database, the items can be arranged according to thecategory of items, past trip history, past packing data, etc.Preferably, a recommended list is presented based on user preferences,and travel-related factors such as destination condition, destinationactivities, and travel mode. In step 101, the user can select theplurality of items that the user would like to pack. The user can alsoselect a container (e.g., a luggage bag, suitcase, luggage, etc.) forpacking. Preferably, a plurality of items can be presented to the userbased on travel related factors and past user packing data and the usercan edit the list accordingly.

Although the term “wardrobe” generally refers to clothing, it is notedthat the wardrobe database further comprises all items that can bepacked such as electronics, personal care items, hygiene items, etc.

In step 102, a packing order of the plurality of items that are selectedin step 101 is optimized based on the packing preference data and itemdata. Step 102 finds a best way (e.g., optimal) of packing each item andits placement in the luggage bag taking other items and their packingpreferences into consideration.

In one embodiment, if a number of items to pack is large and the userdoes not have packing preference data such as a crease of the items or aplacement of the items such that the packing preference of the user isspace-efficient packing, then a packing order to optimally use the spaceof the luggage bag is created in step 102. In other words, step 102 canoptimize the packing order based on both the packing preference data(e.g., maximize space) and item data (e.g., how to arrange/fold eachitem to use a minimum amount of space).

In one embodiment, if a number of items to pack is moderate to large,and the packing preference data of some of the items is that item mustbe crease-free, then, the packing order can be optimized to partitionthe luggage bag into a portion for the items to optimize space and aportion for the items not to include creases (e.g., a left side of theluggage bag includes folded items in any manner to optimize space andthe right side includes a stacked set of folded clothes to avoidcreases). Therefore, step 102 can optimize the packing order based on acombination of packing preference data (e.g., maximize space andminimize creases) and item data (e.g., how to arrange/fold each item touse a minimum amount of space).

It is noted that the packing order can comprise a step-by-stepinstruction for packing each item including how to prepare each item(e.g., folding, wrapping, etc.) for the luggage bag as well as aplacement of the item in the luggage bag. For example, the packing orderincludes a step-by-step instruction for each item on how to fold an itemand where to place the item in the luggage bag. The packing order canfurther account for a weight of the items so as not to harm other itemsby placing heavier items on top.

In step 103, an interactive, augmented video depicting (e.g., visuallyshowing) how to perform the optimized packing order is created. Theinteractive video comprises, for example, a montage of the step-by-stepinstructions for packing each item in order, according to the optimizedpacking order of step 102.

Each type of item can correspond to a pre-made instructional videosegment on how to prepare the item to be placed into the luggage. Thepre-made instruction video can comprise folding instructions, where toplace the item in the luggage bag, etc. The interactive augmented videocomprises each of the pre-made instructional video segmentscorresponding to the items in the packing order according to the orderof the optimized packing order. That is, once step 102 optimizes thepacking order of the plurality of items (e.g., finds out the best way topack each item and its placement in the luggage bag), step 103 createsan interactive augmented video which shows the way of packing eachcontent step by step.

The interactive augmented video can be displayed on any devicecomprising a display for playing the video and an image-capturing devicefor step 104 as described later. However, an external image-capturingdevice utilized with step 104 can be provided and connected to a displaydevice for playing the video.

In step 104, the users' packing process is monitored via theimage-capturing device to display a step of the packing order in theinteractive augmented video based on the item that the user is currentlypacking. In other words, the users' packing process is monitored toconfirm a correctness of the previous step of the optimized order as theuser finishes packing a particular item in the packing order accordingto the step-by-step instructions of the video and triggers the video todisplay the next step of the optimized order.

In one embodiment, step 104 can use a camera to continuously monitor astate of the luggage bag and accordingly guide the user to pack items.That is, once a step is followed and the item is correctly placed in theluggage bag, step 104 automatically recognize the state of the luggagebag (e.g., because of continuous monitoring using a camera) and shows astep to pack a next item to the user in the video.

FIG. 2 depicts a . . . As depicted, in step 104 a, the camera recognizesa current state of the luggage bag and step 104 b determines if thecurrent state matches a state intended at the conclusion of the previousstep (e.g., does the item in the luggage bag match the intended packingorder). If “NO”, the previous step is shown again in the video in step104 c. If “YES”, the next step in the packing order of the video isshown in step 104 d. After step 104 d shows the next step of the video,step 104 a monitors the luggage bag again to repeat steps 104 a-104 duntil the step-by-step instructions of the video have been completedcorrectly.

FIG. 3 depicts an exemplary implementation of the method 100. Packingand folding steps 301-306 of FIG. 3 depict a step-by-step instruction ofa single instruction to fold a shirt of the interactive augmented video.That is, steps 301-306 are determined in step 103. As the video plays,the user follows steps 301-306 to fold the shirt and place the shirtinside (into) the luggage bag. The current state of the luggage bag isrecognized by a camera to determine if the current state of the luggagebag (e.g., where the user placed the item and how the user folded theitem) match the intended location of the optimized packing order. If“YES”, then the video continues to display the next step until thepacking order is complete.

Referring to FIG. 1, in step 105, packing preference data is learned tomodify the packing order based on user preference data over time (e.g.,user modifying the packing order, packing preference data, etc.) andcrowd sourcing from other users.

Crowd sourcing can be performed by a web crawl to learn the itempreferences. For example, documents which mention user's experienceswith different items while travelling and packing can be mined to learnand update item preferences. For example, if a bottle of cologne brokein the luggage bag and a user blogged about this accident, the data canbe mined and that type of cologne can be updated to be packeddifferently to avoid breaking.

User preferences can be given greater weight than crowd sourcingpreferences. However, recommendations may be made to the user based on auser specified crowd sourcing preferences.

That is, by referring to packing habits of other users, in step 105,what type of packing preferences the user has can be learned based onhow the preference of an item evolves over the time. In addition,packing habits can be monitored such that item preferences can belearned relating to which particular items to pack based on a locationof travel. In one embodiment, if a user is travelling to a new place,using the packing preferences of other users who travelled to thatplace, some necessary items can be intelligently recommended to bepacked.

In one embodiment, an interaction with the augmented packing video canbe analyzed to learn whether the packing is done as per therecommendation. If the user deviates from the packing order or steps,item preferences can be learned to reflect the deviations in futurepacking orders.

In some embodiments, determining one or more optimal dimensions, packingpreferences, and priorities of the items to packed can be leveragedthrough cognitive Internet of Things (IoT)-devices. Thus, optimalpacking with improved outcomes is facilitated by an interactive videothat demonstrates a step-by-step procedure for effectively packing inone or more scenarios. Some embodiments can also monitor the user'spacking (e.g., using a camera) and suggest corrections if the user isdeviating from the suggested packing steps in the video.

Exemplary Aspects, Using a Cloud Computing Environment

Although this detailed description includes an exemplary embodiment ofthe present invention in a cloud computing environment, it is to beunderstood that implementation of the teachings recited herein are notlimited to such a cloud computing environment. Rather, embodiments ofthe present invention are capable of being implemented in conjunctionwith any other type of computing environment now known or laterdeveloped.

Cloud computing is a model of service delivery for enabling convenient,on-demand network access to a shared pool of configurable computingresources (e.g. networks, network bandwidth, servers, processing,memory, storage, applications, virtual machines, and services) that canbe rapidly provisioned and released with minimal management effort orinteraction with a provider of the service. This cloud model may includeat least five characteristics, at least three service models, and atleast four deployment models.

Characteristics are as follows:

On-demand self-service: a cloud consumer can unilaterally provisioncomputing capabilities, such as server time and network storage, asneeded automatically without requiring human interaction with theservice's provider.

Broad network access: capabilities are available over a network andaccessed through standard mechanisms that promote use by heterogeneousthin or thick client platforms (e.g., mobile phones, laptops, and PDAs).

Resource pooling: the provider's computing resources are pooled to servemultiple consumers using a multi-tenant model, with different physicaland virtual resources dynamically assigned and reassigned according todemand. There is a sense of location independence in that the consumergenerally has no control or knowledge over the exact location of theprovided resources but may be able to specify location at a higher levelof abstraction (e.g., country, state, or datacenter).

Rapid elasticity: capabilities can be rapidly and elasticallyprovisioned, in some cases automatically, to quickly scale out andrapidly released to quickly scale in. To the consumer, the capabilitiesavailable for provisioning often appear to be unlimited and can bepurchased in any quantity at any time.

Measured service: cloud systems automatically control and optimizeresource use by leveraging a metering capability at some level ofabstraction appropriate to the type of service (e.g., storage,processing, bandwidth, and active user accounts). Resource usage can bemonitored, controlled, and reported providing transparency for both theprovider and consumer of the utilized service.

Service Models are as Follows:

Software as a Service (SaaS): the capability provided to the consumer isto use the provider's applications running on a cloud infrastructure.The applications are accessible from various client circuits through athin client interface such as a web browser (e.g., web-based e-mail) Theconsumer does not manage or control the underlying cloud infrastructureincluding network, servers, operating systems, storage, or evenindividual application capabilities, with the possible exception oflimited user-specific application configuration settings.

Platform as a Service (PaaS): the capability provided to the consumer isto deploy onto the cloud infrastructure consumer-created or acquiredapplications created using programming languages and tools supported bythe provider. The consumer does not manage or control the underlyingcloud infrastructure including networks, servers, operating systems, orstorage, but has control over the deployed applications and possiblyapplication hosting environment configurations.

Infrastructure as a Service (IaaS): the capability provided to theconsumer is to provision processing, storage, networks, and otherfundamental computing resources where the consumer is able to deploy andrun arbitrary software, which can include operating systems andapplications. The consumer does not manage or control the underlyingcloud infrastructure but has control over operating systems, storage,deployed applications, and possibly limited control of select networkingcomponents (e.g., host firewalls).

Deployment Models are as follows:

Private cloud: the cloud infrastructure is operated solely for anorganization. It may be managed by the organization or a third party andmay exist on-premises or off-premises.

Community cloud: the cloud infrastructure is shared by severalorganizations and supports a specific community that has shared concerns(e.g., mission, security requirements, policy, and complianceconsiderations). It may be managed by the organizations or a third partyand may exist on-premises or off-premises.

Public cloud: the cloud infrastructure is made available to the generalpublic or a large industry group and is owned by an organization sellingcloud services.

Hybrid cloud: the cloud infrastructure is a composition of two or moreclouds (private, community, or public) that remain unique entities butare bound together by standardized or proprietary technology thatenables data and application portability (e.g., cloud bursting forload-balancing between clouds).

A cloud computing environment is service oriented with a focus onstatelessness, low coupling, modularity, and semantic interoperability.At the heart of cloud computing is an infrastructure comprising anetwork of interconnected nodes.

Referring specifically now to FIG. 4, a schematic of an example of acloud computing node is shown. Cloud computing node 10 is only oneexample of a suitable node and is not intended to suggest any limitationas to the scope of use or functionality of embodiments of the inventiondescribed herein. Regardless, cloud computing node 10 is capable ofbeing implemented and/or performing any of the functionality set forthherein.

Although cloud computing node 10 is depicted as a computer system/server12, it is understood to be operational with numerous other generalpurpose or special purpose computing system environments orconfigurations. Examples of well-known computing systems, environments,devices and/or configurations that may be suitable for use with computersystem/server 12 include, but are not limited to, client computersystems, computer workstations, other computer servers, thin clients,thick clients, hand-held devices, laptop devices, mobile devices,multiprocessor systems, microprocessor-based systems, set top boxes,consumer electronics, network devices, minicomputer systems, mainframecomputer systems, and distributed cloud computing nodes and environmentsthat include any of the above systems or circuits, and the like.

Computer system/server 12 may be described in the general context ofcomputer system-executable instructions, such as program modules, beingexecuted by a computer system. Generally, program modules may includeroutines, programs, objects, components, logic, data structures, and soon that perform particular tasks or implement particular abstract datatypes. Computer system/server 12 may be practiced in distributed cloudcomputing environments where tasks are performed by remote processingcircuits that are linked through a communications network. In adistributed cloud computing environment, program modules may be locatedin both local and remote computer system storage media including memorystorage circuits.

Referring again to FIG. 4, computer system/server 12 is shown in theform of a general-purpose computing circuit. The components of computersystem/server 12 may include, but are not limited to, one or moreprocessors or processing units 16, a system memory 28, and a bus 18 thatcouples various system components including system memory 28 toprocessor 16.

Bus 18 represents one or more of any of several types of bus structures,including a memory bus or memory controller, a peripheral bus, anaccelerated graphics port, and a processor or local bus using any of avariety of bus architectures. By way of example, and not limitation,such architectures include Industry Standard Architecture (ISA) bus,Micro Channel Architecture (MCA) bus, Enhanced ISA (EISA) bus, VideoElectronics Standards Association (VESA) local bus, and PeripheralComponent Interconnects (PCI) bus.

Computer system/server 12 typically includes a variety of computersystem readable media. Such media may be any available media that isaccessible by computer system/server 12, and it includes both volatileand non-volatile media, removable and non-removable media.

System memory 28 can include computer system readable media in the formof volatile memory, such as random access memory (RAM) 30 and/or cachememory 32. Computer system/server 12 may further include otherremovable/non-removable, volatile/non-volatile computer system storagemedia. By way of example only, storage system 34 can be provided forreading from and writing to a non-removable, non-volatile magnetic media(not shown and typically called a “hard drive”). Although not shown, amagnetic disk drive for reading from and writing to a removable,non-volatile magnetic disk (e.g., a “floppy disk”), and an optical diskdrive for reading from or writing to a removable, non-volatile opticaldisk such as a CD-ROM, DVD-ROM or other optical media can be provided.In such instances, each can be connected to bus 18 by one or more datamedia interfaces. As will be further depicted and described below,memory 28 may include at least one program product having a set (e.g.,at least one) of program modules that are configured to carry out thefunctions of embodiments of the invention.

Program/utility 40, having a set (at least one) of program modules 42,may be stored in memory 28 by way of example, and not limitation, aswell as an operating system, one or more application programs, otherprogram modules, and program data. Each of the operating system, one ormore application programs, other program modules, and program data orsome combination thereof, may include an implementation of a networkingenvironment. Program modules 42 generally carry out the functions and/ormethodologies of embodiments of the invention as described herein.

Computer system/server 12 may also communicate with one or more externaldevices 14 such as a keyboard, a pointing circuit, a display 24, etc.;one or more circuits that enable a user to interact with computersystem/server 12; and/or any circuits (e.g., network card, modem, etc.)that enable computer system/server 12 to communicate with one or moreother computing circuits. Such communication can occur via Input/Output(I/O) interfaces 22. Still yet, computer system/server 12 cancommunicate with one or more networks such as a local area network(LAN), a general wide area network (WAN), and/or a public network (e.g.,the Internet) via network adapter 20. As depicted, network adapter 20communicates with the other components of computer system/server 12 viabus 18. It should be understood that although not shown, other hardwareand/or software components could be used in conjunction with computersystem/server 12. Examples, include, but are not limited to: microcode,circuit drivers, redundant processing units, external disk drive arrays,RAID systems, tape drives, and data archival storage systems, etc.

FIG. 5 depicts an embodiment of a cloud computing environment inaccordance with the present invention. As depicted, cloud computingenvironment 50 comprises one or more cloud computing nodes 10 with whichlocal computing circuits used by cloud consumers, such as, for example,personal digital assistant (PDA) or cellular telephone 54A, desktopcomputer 54B, laptop computer 54C, and/or automobile computer system 54Nmay communicate. Nodes 10 may communicate with one another. They may begrouped (not shown) physically or virtually, in one or more networks,such as Private, Community, Public, or Hybrid clouds as describedhereinabove, or a combination thereof. This allows cloud computingenvironment 50 to offer infrastructure, platforms and/or software asservices for which a cloud consumer does not need to maintain resourceson a local computing circuit. It is understood that the types ofcomputing circuits 54A-N shown in FIG. 5 are intended to be illustrativeonly and that computing nodes 10 and cloud computing environment 50 cancommunicate with any type of computerized circuit over any type ofnetwork and/or network addressable connection (e.g., using a webbrowser).

FIG. 6 depicts an exemplary set of functional abstraction layersprovided by the cloud computing environment 50 (FIG. 5). It should beunderstood in advance that the components, layers, and functions shownin FIG. 6 are intended to be illustrative only and embodiments of theinvention are not limited thereto. As depicted, the following layers andcorresponding functions are provided:

Hardware and software layer 60 includes hardware and softwarecomponents. Examples of hardware components include: mainframes 61; RISC(Reduced Instruction Set Computer) architecture based servers 62;servers 63; blade servers 64; storage circuits 65; and networks andnetworking components 66. In some embodiments, software componentsinclude network application server software 67 and database software 68.

Virtualization layer 70 provides an abstraction layer from which thefollowing examples of virtual entities may be provided: virtual servers71; virtual storage 72; virtual networks 73, including virtual privatenetworks; virtual applications and operating systems 74; and virtualclients 75.

In one example, management layer 80 may provide the functions describedbelow. Resource provisioning 81 provides dynamic procurement ofcomputing resources and other resources that are utilized to performtasks within the cloud computing environment. Metering and Pricing 82provide cost tracking as resources are utilized within the cloudcomputing environment, and billing or invoicing for consumption of theseresources. In one example, these resources may comprise applicationsoftware licenses. Security provides identity verification for cloudconsumers and tasks, as well as protection for data and other resources.User portal 83 provides access to the cloud computing environment forconsumers and system administrators. Service level management 84provides cloud computing resource allocation and management such thatrequired service levels are met. Service Level Agreement (SLA) planningand fulfillment 85 provide pre-arrangement for, and procurement of,cloud computing resources for which a future requirement is anticipatedin accordance with an SLA.

Workloads layer 90 provides examples of functionality for which thecloud computing environment may be utilized. Examples of workloads andfunctions which may be provided from this layer include: mapping andnavigation 91; software development and lifecycle management 92; virtualclassroom education delivery 93; data analytics processing 94;transaction processing 95; and, more particularly relative toembodiments of the present invention, a packing method and computerprogram product.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, configuration data for integrated circuitry, oreither source code or object code written in any combination of one ormore programming languages, including an object oriented programminglanguage such as Smalltalk, C++, or the like, and procedural programminglanguages, such as the “C” programming language or similar programminglanguages. The computer readable program instructions may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider). In some embodiments, electronic circuitry including,for example, programmable logic circuitry, field-programmable gatearrays (FPGA), or programmable logic arrays (PLA) may execute thecomputer readable program instructions by utilizing state information ofthe computer readable program instructions to personalize the electroniccircuitry, in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a computer readable storage medium that can directa computer, a programmable data processing apparatus, and/or otherdevices to function in a particular manner, such that the computerreadable storage medium having instructions stored therein comprises anarticle of manufacture including instructions which implement aspects ofthe function/act specified in the flowchart and/or block diagram blockor blocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof instructions, which comprises one or more executable instructions forimplementing the specified logical function(s). In some alternativeimplementations, the functions noted in the blocks may occur out of theorder noted in the Figures. For example, two blocks shown in successionmay, in fact, be executed substantially concurrently, or the blocks maysometimes be executed in the reverse order, depending upon thefunctionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

Further, Applicant's intent is to encompass the equivalents of all claimelements, and no amendment to any claim of the present applicationshould be construed as a disclaimer of any interest in or right to anequivalent of any element or feature of the amended claim.

What is claimed is:
 1. A computer-implemented packing method, the methodcomprising: selecting a plurality of items stored in a memory to packinto a container; generating a packing order of the plurality of itemsbased on packing preference data and item data stored in the memory;creating and displaying a video of step-by-step packing instructions forthe plurality of items in the packing order; monitoring and comparing anactual packing process to a generated packing order; and controllingsaid displaying of step of the step-by-step packing instructions, inresponse to said monitoring and comparing.
 2. The method of claim 1,wherein the item data is selected from a group consisting of: adimension of the plurality of items; a type of each of the items; and afragility of each of the items, and wherein the packing preference datais selected from a group consisting of: a preferred location of an itemin the container; and a preferred condition of the item including acrease or a wrinkle in clothing items.
 3. The method of claim 1, whereinthe step-by-step packing instructions of the video comprise foldinginstructions for one or more of the plurality of items in the packingorder.
 4. The method of claim 1, wherein the packing order is based on adimension of one or more of the plurality of items correlated with adimension of the container.
 5. The method of claim 1, wherein saidmonitoring and comparing further comprises: determining that a step ofthe step-by-step instructions is correctly completed, based on alocation of the item and a preparation of the item matching a locationof the item and a preparation of the item in the step-by-stepinstructions; and playing a next step of the step-by-step instructions,in response to said determining.
 6. The method of claim 1, furthercomprising modifying the packing order based on at least one of a priorpacking order, the packing preference data and crowd sourcing data. 7.The method of claim 1, wherein the step-by-step packing instructions ofthe video comprise a placement for one or more of the plurality of itemsin the container and folding instructions for one or more of theplurality of items.
 8. A computer program product for packing, thecomputer program product comprising a computer readable storage mediumhaving program instructions embodied therewith, the program instructionsexecutable by a computer to cause the computer to perform: selecting aplurality of items stored in a memory to pack into a container;generating a packing order of the plurality of items based on packingpreference data and item data stored in the memory; creating anddisplaying a video of step-by-step packing instructions for theplurality of items in the packing order; monitoring and comparing anactual packing process to a generated packing order; and controllingsaid displaying of step of the step-by-step packing instructions, inresponse to said monitoring and comparing.
 9. The computer programproduct of claim 8, wherein the item data is selected from a groupconsisting of: a dimension of the plurality of items; a type of each ofthe items; and a fragility of each of the items, and wherein the packingpreference data is selected from a group consisting of: a preferredlocation of an item in the container; and a preferred condition of theitem including a crease or a wrinkle in clothing items.
 10. The computerprogram product of claim 8, wherein the step-by-step packinginstructions of the video comprise folding instructions for one or moreof the plurality of items in the packing order.
 11. The computer programproduct of claim 8, wherein the packing order is based on a dimension ofone or more of the plurality of items correlated with a dimension of thecontainer.
 12. The computer program product of claim 8, wherein saidmonitoring and comparing further comprises: determining that a step ofthe step-by-step instructions is correctly completed, based on alocation of the item and a preparation of the item matching a locationof the item and a preparation of the item in the step-by-stepinstructions; and playing a next step of the step-by-step instructions,in response to said determining.
 13. The computer program product ofclaim 8, further comprising modifying the packing order based on atleast one of a prior packing order, the packing preference data andcrowd sourcing data.
 14. The computer program product of claim 8,wherein the step-by-step packing instructions of the video comprise aplacement for one or more of the plurality of items in the container andfolding instructions for one or more of the plurality of items.
 15. Thecomputer program product of claim 8, wherein the computer programproduct is adapted for a cloud-computing environment
 16. A packingsystem, said system comprising: a processor; and a memory, the memorystoring instructions to cause the processor to: select a plurality ofitems stored in a memory to pack into a container; generate a packingorder of the plurality of items based on packing preference data anditem data stored in the memory; create and display a video ofstep-by-step packing instructions for the plurality of items in thepacking order; monitor and compare an actual packing process to agenerated packing order; and control said display of step of thestep-by-step packing instructions, in response to said monitoring andcomparing.
 17. The system of claim 16, wherein the item data comprises:a dimension of the plurality of items; a type of each of the items; anda fragility of each of the items, and wherein the packing preferencedata is selected from a group consisting of: a preferred location of anitem in the container; and a preferred condition of the item including acrease or a wrinkle in clothing items.
 18. The system of claim 16,wherein the step-by-step packing instructions of the video comprisefolding instructions for one or more of the plurality of items in thepacking order.
 19. The system of claim 16, wherein the packing order isbased on a dimension of one or more of the plurality of items correlatedwith a dimension of the container.
 20. The system of claim 16, embodiedin a cloud-computing environment.